Part 5: Results and Conclusion

Introduction

What the problem is:

  • scope
  • next

Summary of Results

DC minutes Philly minutes NYC minutes DC miles Philly miles NYC miles
Min 0.00000 0.00000 0.0000 0.000000 0.000000 0.000000
1st Qu 55.30000 80.31667 83.1500 4.250792 6.364693 11.294021
Median 72.03333 107.78333 111.7500 6.877634 10.163438 18.151150
Mean 72.52182 116.91172 117.0508 7.119155 10.623455 19.113244
3rd Qu 89.18333 138.43333 141.0000 9.775393 14.337647 26.475954
Max 163.83333 516.33333 1316.0500 19.387365 41.823172 68.265572
St. Dev. 24.61760 61.82033 79.8526 3.620629 5.549423 9.939558

What to say here:

  • dc looking good
    • least amount of skew (look at that close mean and median)
    • lowest everything
    • learned later on that this is partially due to DC
  • NY and Philly are pretty close
    • ew, look at those max values (we’ll look at that soon)
  • the difference in sd between minutes and miles is interesting
    • maybe google how to look into that

histograms

Clearly some issues with NY and philadelphia:

  • as suspected, DC is beautiful
  • the skew of Philly and NYC is surprisingly bad

scatterplots

Looking at these summary statistics and histogram, I would like to put forward an axiom:

Any trip over three hours, in this situation, can be defined as “Shit Luck”

good points are in light blue, Bad points are in dark blue, truly evil points in black:

  • let’s split this shit up
    • normal < 180
    • 180 < bad < 300
    • evil > 300

Percent of Bad Trips

DC PH NY
3 hour trip 0.00 8.12 5.98
2 hour trip 2.96 38.85 42.65

Here I will talk about
this shit cause
Im dope as fuck it is the percent of bad trips in each city

Here are the scatterplots of only trips less than 3 hours shows a pretty nice casual relationship discuss each DC being a tiny city is hugely helpful

The “bad luck” trips

Both New York City and Philadelphia have some weird clusters of points evident from their scatter plot. Let’s look at the trips that take more than 400 minutes.

start_latitude Freq end_latitude Freq start_latitude Freq end_latitude Freq
39.8888 288 39.8888 94 40.5404671945649 259 NA NA
39.9010033 93 39.8911694 18 NA NA NA
40.0535197 33 39.9755981 3 NA NA NA
39.8840912 2 40.0324002 3 NA NA NA
39.9413149 2 40.0514994 3 NA NA NA
39.9541915 2 40.0526994 3 NA NA NA

Here:

  • several points in Philly
  • Only 1 in NYC
  • WTF is up with these points?

The EVIL NY POINT

Here is:

  1. The routes
  2. That one point everything is going towards

Philadelphia

Here is:

  1. The routee
  2. there are several points that everything comes/goes to
  3. see leaflet and rewrite

What’s happening here:

  1. I have take a sample of 50 routes from the top 10% of trips, bottom 10% of cities, and middle 50
  2. plotted those routes

Sample of Short, Medium, and Long Trips

Neighborhoods individual

okay so app being in the rivers or oceans can be both really negative and realy positive



One of the coolest things about NYC is the spread of the best locations to start. DC and Philly, they’re very bunched up.